Research Article
Partially Overlapping Channel Selection in Jamming Environment: A Hierarchical Learning Approach
@INPROCEEDINGS{10.1007/978-3-030-32388-2_12, author={Lei Zhao and Jincheng Ge and Kailing Yao and Yifan Xu and Xiaobo Zhang and Menglan Fan}, title={Partially Overlapping Channel Selection in Jamming Environment: A Hierarchical Learning Approach}, proceedings={Machine Learning and Intelligent Communications. 4th International Conference, MLICOM 2019, Nanjing, China, August 24--25, 2019, Proceedings}, proceedings_a={MLICOM}, year={2019}, month={10}, keywords={Intelligent anti-jamming Stackelberg game Channel selection Partially overlapping channel}, doi={10.1007/978-3-030-32388-2_12} }- Lei Zhao
Jincheng Ge
Kailing Yao
Yifan Xu
Xiaobo Zhang
Menglan Fan
Year: 2019
Partially Overlapping Channel Selection in Jamming Environment: A Hierarchical Learning Approach
MLICOM
Springer
DOI: 10.1007/978-3-030-32388-2_12
Abstract
This paper solves the channel selection with anti-jamming problem using partially overlapping channel (POC) in limited spectrum environment. Since it is difficult for users to obtain global information of networks, this paper realizes the coordination of channel access by the local information interaction. The channel selection with anti-jamming problem is formulated as a Stackelberg game where the jammer acts as leader and users act as followers. We prove that the game model exists at least one Stackelberg equilibrium (SE) solution. To achieve the equilibrium, a hierarchical learning algorithm (HLA) is proposed. Based on the proposed method, the system can achieve the improvement of throughput performance by minimizing local interference. Simulation results show the proposed algorithm can achieve good performance under jamming environment, and the network throughput can maintain a stable state with the jamming intensity increasing.